Systems and methods for intelligent, demand-responsive transit recommendations

Abstract

Techniques and systems are described that enable the intelligent recommendation and presentation of demand-responsive transit services. Implementations can analyze current user activities with respect to historically-based user transit behaviors in order to determine the user's imminent transit demands. Prior-scheduled transit options meeting the imminent demand are searched, and filtering parameters including user preferences and demand-responsive transit provider constraints are retrieved. Embodiments further retrieve possible demand-responsive transit options for meeting the demand from a demand-responsive transit system scheduling / information service. Embodiments consolidate and analyze these diverse sources to identify a set of preferred transit alternatives for available transit options that meet the filtering parameters. Implementations are described that integrate with an existing transit application present on a user device (e.g., a mobile device). Certain embodiments may include capabilities for surfacing an enhanced transit options view that shows an identified imminent transit demand and a selection of preferred transit alternatives.

Description

GOVERNMENT SUPPORT[0001]This invention was made with government support under grant numbers I / UCRC IIP-1338922, AIR IIP-1237818, III-Large IIS-1213026, MRI CNS-1532061, CREST HRD-0833093 awarded by the National Science Foundation. The government has certain rights in the invention.BACKGROUND[0002]Generally, a transit system is a large-scale public transportation system serving a given area, typically comprising buses, subways, and elevated trains. A transit system usually has numerous transit lines which represent pathways through the given area from a starting point to an ending point through various intermediate stopping points. One or more transit vehicles can service a particular transit line, generally several times a day.[0003]Many travelers are creatures of habit, using the same transit modes and routes on the transit system every day to minimize the impact of unfamiliar surroundings and traveling modes. Therefore, it can be difficult to get users to adapt to new transit serv...

AI Technical Summary

Benefits of technology

The patent text describes a system that uses data from users to improve recommendations for preferred transit alternatives. This helps to expand the user base for demand-responsive transit systems and make them more user-friendly. By collecting and utilizing user feedback, the system creates an improved user experience and reduces inefficiencies in the transit system. This can result in energy savings and reduced emissions output, benefitting both the user and the city or region where the transit system is located.

Problems solved by technology

Traditionally, DRT systems provide a public transport service for areas of low passenger demand, such as rural areas, where a regular bus service would not be viable.

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